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510(k) Data Aggregation

    K Number
    K192652
    Device Name
    TRV
    Manufacturer
    Interacoustics A/S
    Date Cleared
    2020-05-27

    (246 days)

    Product Code
    LXV
    Regulation Number
    N/A
    Type
    Traditional
    Panel
    Ear Nose & Throat
    Reference & Predicate Devices
    K071973
    Why did this record match?
    Device Name :

    TRV

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The TRV is intended to assist in the diagnosis and treatment of balance disorders and vertigo, including benign paroxysmal positional vertigo.

    Device Description

    The TRV is a multi-axial chair that can rotate 360° around both the horizontal and vertical axes. With the patient secured by a four-point harness, a head mount, a leg strap, and shoulder pads, an examiner is able to rotate the patient around the plane of each of the 6 semicircular canals and hold the patient in any position for detailed examination of the semicircular canals. The TRV chair is manually handled by the healthcare professional. The axes of rotation are lockable in preset positions. The primary axis has a battery-powered electromagnetic lock controlled by a footswitch and the secondary axis is manually locked with a mechanical lever. A mechanical system with an adjustable counterweight ensures that the weight of the chair and the patient are balanced during the maneuvers.

    AI/ML Overview

    The provided text describes the TRV device and its substantial equivalence to a predicate device, the Epley Omniax™. However, it does not contain information related to a study that establishes acceptance criteria and then proves the device meets those criteria, especially in the context of an AI-powered device or for clinical accuracy.

    Instead, the document details a 510(k) submission for a physical medical device (a multi-axial chair) used in the diagnosis and treatment of balance disorders. The performance data presented focuses on electrical safety, electromagnetic compatibility, and mechanical testing, not on predictive performance, accuracy, or diagnostic effectiveness in the way an AI/software device would be evaluated.

    Therefore, many of the requested elements for describing "acceptance criteria and the study that proves the device meets the acceptance criteria" in an AI/software context are not present in the provided document.

    Here's a breakdown of what can and cannot be answered based on the provided text:

    1. Table of acceptance criteria and the reported device performance

    Acceptance Criteria (General Safety and Performance)Reported Device Performance
    Electrical Safety: Comply with IEC 60601-1Passed: Device complies with IEC 60601-1 for electrical safety.
    Electromagnetic Compatibility (EMC): Comply with IEC 60601-1-2Passed: Device complies with IEC 60601-1-2 standard for EMC.
    Mechanical Testing: Demonstrate long-term safety and withstand worst-case stress loads.Passed: Wear observed after testing is considered not to have any effect on the safety of patients or operators.
    Technological Equivalence (to predicate device): Similar indications for use, use environment, user, patient population, test options, maneuvers, movement range, and power supply (with supported differences).Achieved: Found to be as safe, as effective, and performs comparably to the predicate device, with technological differences supported by non-clinical data.

    2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    • Not Applicable / Not Provided: The document does not describe a "test set" in the context of data for an algorithm. The "testing" refers to physical device safety and mechanical performance. There is no data provenance for a diagnostic or predictive model.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    • Not Applicable / Not Provided: No "ground truth" establishment for a diagnostic output is described, as this is a physical chair, not an AI diagnostic tool.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

    • Not Applicable / Not Provided: No adjudication method for a data test set is described.

    5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

    • No: A multi-reader multi-case (MRMC) study was not done. The device is a physical chair, not an AI assistant.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

    • No: This is not an algorithm. The device is a physical chair, and human healthcare professionals manually operate it. Its function is to assist professionals in performing maneuvers, not to make a standalone diagnosis or treatment decision without human input.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

    • Not Applicable / Not Provided: See point 3. The "ground truth" in this context pertains to compliance with safety regulations and functional equivalence to a predicate device, not diagnostic accuracy.

    8. The sample size for the training set

    • Not Applicable / Not Provided: No training set is described, as this is a physical device and not an AI model.

    9. How the ground truth for the training set was established

    • Not Applicable / Not Provided: No training set or ground truth establishment for it is described.
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